Analysing Bicycle Sharing System User Destination Choice Preferences: An Investigation of Chicago’s Divvy System

In recent years, there has been increasing attention on bicycle-sharing systems (BSS) as a viable and sustainable mode of transportation for short trips. However, due to relatively recent adoption of BSS there is very little research exploring how people consider these systems within the existing transportation alternatives. Given the recent growth of BSS across the world, there is substantial interest in identifying contributing factors that encourage individuals to use these systems. The current study contributes to the growing literature by examining BSS behavior at a trip level to analyze bicyclists’ destination preferences. Specifically, we study the decision process involved in identifying destination locations after picking up a bicycle at a BSS station using a random utility maximization approach in the form of a multinomial logit model (MNL). The quantitative frameworks developed have been estimated using data from Chicago’s Divvy system for 2013. In our modeling effort, we distinguish between BSS users with annual membership and short-term customers with daily passes. The developed model will allow bicycle-sharing system operators to better plan their services by examining the impact of travel distance, land use, built environment and access to public transportation infrastructure on users’ destination preferences. Using the estimated model we generate utility profiles as a function of distance and various other attributes allowing us to visually represent the trade-offs that individuals make in their decision process. To further illustrate the applicability of the proposed framework for planning purposes, destination station choice probability prediction is undertaken.